There are two ideas of AI:
- ANI (Artificial Narrow Intelligence): E.g., smart speaker, self-driving car and web search.
- AGN (Artificial General Intelligence): do anything a human can do.
ANI is realistic and incredibly valuable. Though AGN is still too far away, and there is no need to unduly worry about it.
When talking about data in term of AI that means talking about dataset. There are several methods to get a dataset:
- Manual labeling
- Observing user behaviors
- Observing behaviors of other things such as machine
- Downloading dataset from a website or acquiring it from a partner.
Machine learning (ML) is a tool in AI. Supervised learning is a type of ML that learns A to B, or input to output mappings. Deep learning/Neural networks is a type of supervised learning which can maximize the performance of AI when dataset is big today.
Is AI a subset of data science?
No! Data science uses many tools from AI machine learning, but has some other separate tools as well that solves a very set of important problems in driving business insights.
- ML project output: a running AI system
- Data science project output: a set of insights